Product Discovery is Changing

Customers no longer expect product discovery to simply return a list of matching products. They expect shopping experiences that understand intent, answer questions, recommend alternatives, and help them make better purchasing decisions.

Personalized relevance has become the new baseline. Every interaction should reflect customer behavior, inventory, merchandising priorities, and business objectives, while continuously adapting as those signals change. As AI reshapes digital commerce, search, recommendations, personalization, merchandising, and conversational shopping are converging into a single product discovery experience.

Vespa brings these capabilities together in a unified platform, helping retailers improve customer engagement today while supporting the next generation of intelligent shopping experiences.

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The Vespa platform

Product Discovery Capabilities

Vespa unifies search, recommendations, merchandising, personalization, and AI in a single platform for intelligent shopping experiences.

  • Search

    Hybrid keyword and semantic search combine precise lexical matching with natural language understanding, structured product attributes, and business rules to deliver accurate product discovery across both B2C and B2B catalogs.

    Explore search

  • Recommendations

    Deliver personalized recommendations using real-time behavioral signals, customer context, inventory, and merchandising priorities to continuously improve engagement and conversion.

    Explore recommendations

  • Ranking & Merchandising

    Balance machine-learned relevance with business strategy. Apply merchandising rules, promotional campaigns, inventory awareness, and ranking models together without sacrificing relevance or operational agility.

    Explore multi-signal ranking

  • Conversational Shopping

    Enable AI-powered shopping assistants that understand customer intent, answer product questions, compare alternatives, and guide purchasing decisions using your proprietary product catalog and business knowledge.

    Explore conversational shopping

  • Agentic Commerce

    Support the next generation of AI shopping agents by providing fast, accurate access to product information, inventory, pricing, and business rules through a unified product discovery platform.

    Explore agentic commerce

Vinted

Vinted transitioned to Vespa to enhance the performance and scalability of their search and recommendation systems. Vespa’s ability to handle complex, large-scale data and to support machine learning models natively enabled Vinted to deliver faster, more personalized search results.

Read the case study

key considerations

Business Challenges

Modern product discovery requires retailers to balance customer relevance, commercial objectives, rapid experimentation, and platform performance. Vespa helps bring these competing priorities together within a single product discovery platform. Explore each challenge to see how Vespa helps.

Customers no longer compare your search experience with other retailers. They compare it with the personalized experiences they receive every day from streaming platforms, social media, and AI assistants. Every interaction is expected to reflect customer intent, preferences, location, browsing history, and real-time context.

Delivering this level of relevance requires search, recommendations, and personalization to work together rather than operating as separate systems. The challenge is maintaining a consistent experience while customer behavior, inventory, and business priorities continually change.

Vespa combines these signals within a single product discovery platform, enabling retailers to continuously adapt relevance without increasing operational complexity.

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Choose Vespa When

  • Product discovery is becoming a strategic competitive advantage for your business.
  • Customer expectations are outgrowing traditional search and recommendation technologies.
  • You need to balance AI innovation with merchandising control and commercial objectives.
  • Personalization must adapt continuously to customer behavior, inventory, and business priorities.
  • You want to simplify your commerce stack rather than add more disconnected AI services.
  • You need a platform that grows with your ambitions, from better search and recommendations to conversational and agentic commerce.

Why Vespa?

Unlike point solutions that address individual aspects of product discovery, Vespa combines search, recommendations, ranking, personalization, and AI within a single platform.

By unifying retrieval, ranking, machine learning, and real-time serving, Vespa enables retailers to deliver intelligent shopping experiences while reducing operational complexity and controlling infrastructure costs.

Whether you're modernizing search, improving recommendations, or introducing conversational and agentic shopping experiences, Vespa provides a common foundation that evolves with your business.

Who is Vespa For?

Whether you're responsible for growing revenue or delivering the technology behind modern product discovery, Vespa helps retailers deliver more relevant, intelligent shopping experiences.

Different teams have different priorities, but they all depend on the same product discovery platform to deliver exceptional customer experiences.

Explore how Vespa supports business and technical teams.

Explore the AI Search Platform

Modern product discovery depends on more than search alone.Learn how Vespa brings retrieval, ranking, machine learning, and real-time serving together in a single architecture designed for intelligent product discovery at scale.

Explore the AI Search Platform

Ready to Modernize Product Discovery?

Whether you're improving search, recommendations, personalization, or exploring conversational and agentic shopping experiences, we'd be happy to discuss your goals and how Vespa can help you build the next generation of product discovery.

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